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machine learning deep learning natural language processing deep neural networks nlp bayes theorem neural networks probability theory image classification ai convolutional neural networks word representation joint probability distributions language model word2vec add 1 smoothing computer vision artificial intelligence classification problems linear models convolution cnn regression problems recurrent neural network cosine similarity lemmatization stemming named entity recognition maxent ner maximum entropy models tagging rnn tokenization nlp applications deep learning for practitioners practical deep learning feature learning bidirectional rnn restricted boltzmann machines lstm autoencoders long short term memory introduction to deep learning gru gated recurrent units primer n-grams distributed representation baysean networks wordnet smoothing techniques discounting interpolation dynamic programming algorithm applications of minimum edit distance edit distance minimum edit distance text normalization viterbi algorithm hmm baum welch algorithm words hidden markov model forward algorithm backward algorithm forward backward algorithm loglinear bayes networks random variables gaussian sum rule of probability product rule of probability naive bayes classifier conditional independence independence generative models gaussian naive bayes overfitting underfitting bias variance relu sigmoid adagrad backpropagation resnet imagenet localization googlenet inception senet generative adversarial networks gan cyclegan sagan image to image translation conditional gan unsupervised learning decision surface perceptron learning supervised learning decision tree information gain entropy id3 algorithm deep learning frameworks theano tensorflow deep neural networks for speech speech synthesis speech recognition memory networks neural turing machine lsa svd singular value decomposition latent semantic analysis introduction overview robotics search problems bfs dfs a star uniform cost search state space graph search